1,797 questions
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Linear model with random variable [migrated]
I am trying to run a linear model to investigate whether chick SMI correlates with the parent's number of foraging trips with package lme4 in R.
Since chicks can come from the same parent, I struggle ...
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56
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Can I use the segmented package with a generalized linear mixed model?
I am working on a grant proposal evaluating the effectiveness of an intervention on several different groups of hospitals and after some statistical consulting have landed on using a generalized ...
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44
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step() and mixed model in R [closed]
I built my mixed models with function lme4::lmer() and lme4::glmer() and tried to do the stepwise method. Unfortunately step() or stepAIC() didn't work with lme4::lmer() neither lme4::glmer(). Did ...
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1
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65
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Why is glmer function for logistic regression taking so long to run in R?
I am running a multiple logistic regression model. The dataset has ~350,000 observations, with the outcome being a binary 0/1 dichotomous variable. Most predictors are also dichotomous but there are ...
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29
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Why won't my multilevel model converge in R (lme4)?
i have a multilevel model at firm and local authority district level, with both firm level and LAD level predictors. It is a binary logistic model, the outcome is presence of women on the board of a ...
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How to bootstrap ANOVA type 3 fixed effects of a linear mixed model in R (lme4)?
I've been trying to bootstrap a linear mixed model with three 2-level categorical fixed factors (and all two-way interactions), and one random factor.
I can get the linear mixed model to run, I can ...
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66
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How to use emmeans for contrast/pairwise comparison when fixed-effect model matrix is rank deficient?
I have a data with 3 fixed effect factors G (two levels g1 and g2), V (two levels v1 and v2) and C (c1,c2,c3,c4,c5,c6,c7), and a random effect ID. I need to fit a linear mixed model or robust lmm with ...
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fixed-effect model matrix is rank deficient so dropping 5 columns / coefficients (lme4 package) after grouping age into four categories
This question appears to be a duplicate, I am however unable to resolve my case by looking at the existing suggestions on my model. I am trying to fit the three-level random intercept model. The idea ...
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2
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133
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Ggplot visualization of Lmer output
I'm trying to visualize lmer output with ggplot, but cannot get the result I want.
The code looks as follows:
model <- lmer(Fluency ~ Roundnr * relevel(as.factor(Condition), ref='C3') * block + (1|...
1
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1
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78
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I get an error when I run my model: "Error in family$family : $ operator not defined for this S4 class"
How do I resolve the error: "Error in family$family : $ operator not defined for this S4 class", when running a zipoisson model in this code? I have tried a poisson model and a quasi poisson ...
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1
answer
50
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Does mediate() in r work with a multicategorical predictor?
My data is multilevel (multiple measures for each participant within each condition) with 3 conditions.
DV = continuous; Mediator = continuous; IV = categorical (with 3 conditions: control, condition ...
2
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2
answers
85
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R commands behave incorrectly when converted to a function: failed evaluation of variable in for loop
I have the following reproducible example, which calculates a simple neighbourhood cross validation on a mixed regression model. As shown, if I turn the group of commands into a function, they behave ...
1
vote
1
answer
30
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glmer singular fit after small change in the data
I'm running univariate analyses to search for biological factors related to my disease outcome. I am dealing with related individuals, meaning I am using glmer adjusting for covariates and family ...
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2
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46
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GLMM - similar estimated means across software but differing fixed effect estimates
I have run a GLMM using glmer (from lme4) in R. The fixed effects estimates are very different (much smaller) than expected in comparison to the estimated marginal means.
GLMM OUTPUT
`Generalized ...
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1
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45
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Workaround for Overfit Model in glmer()
I am analyzing how variable Y increases with variable X with a random intercept based on Z. Currently, I have this model fit:
m1 <- glmer(Y ~ scale(X) + (1 | Z),
data = d, family = ...
